Pandas Profiling Report

Dataset statistics

Number of variables	12
Number of observations	1000
Missing cells	192
Missing cells (%)	1.6%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	74.3 KiB
Average record size in memory	76.1 B

Variable types

Numeric	7
Categorical	5

Warnings

`title` has a high cardinality: 999 distinct values	High cardinality
`genre` has a high cardinality: 207 distinct values	High cardinality
`description` has a high cardinality: 1000 distinct values	High cardinality
`director` has a high cardinality: 644 distinct values	High cardinality
`actors` has a high cardinality: 996 distinct values	High cardinality
`revenue (millions)` has 128 (12.8%) missing values	Missing
`metascore` has 64 (6.4%) missing values	Missing
`rank` is uniformly distributed	Uniform
`title` is uniformly distributed	Uniform
`description` is uniformly distributed	Uniform
`director` is uniformly distributed	Uniform
`actors` is uniformly distributed	Uniform
`rank` has unique values	Unique
`description` has unique values	Unique

Reproduction

Analysis started	2021-01-30 16:31:40.415377
Analysis finished	2021-01-30 16:31:54.978053
Duration	14.56 seconds
Software version	pandas-profiling v2.10.0
Download configuration	config.yaml

rank
Real number (ℝ_≥0)

UNIFORM
UNIQUE

Distinct	1000
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	500.5
Minimum	1
Maximum	1000
Zeros	0
Zeros (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	1
5-th percentile	50.95
Q1	250.75
median	500.5
Q3	750.25
95-th percentile	950.05
Maximum	1000
Range	999
Interquartile range (IQR)	499.5

Descriptive statistics

Standard deviation	288.8194361
Coefficient of variation (CV)	0.5770618104
Kurtosis	-1.2
Mean	500.5
Median Absolute Deviation (MAD)	250
Skewness	0
Sum	500500
Variance	83416.66667
Monotocity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1000	1	0.1%
329	1	0.1%
342	1	0.1%
341	1	0.1%
340	1	0.1%
339	1	0.1%
338	1	0.1%
337	1	0.1%
336	1	0.1%
335	1	0.1%
Other values (990)	990	99.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	1	0.1%
2	1	0.1%
3	1	0.1%
4	1	0.1%
5	1	0.1%

Value	Count	Frequency (%)
1000	1	0.1%
999	1	0.1%
998	1	0.1%
997	1	0.1%
996	1	0.1%

title
Categorical

HIGH CARDINALITY
UNIFORM

Distinct	999
Distinct (%)	99.9%
Missing	0
Missing (%)	0.0%
Memory size	4.0 KiB

The Host	2
The Invitation	1
La tortue rouge	1
Big Hero 6	1
Relatos salvajes	1
Other values (994)	994

Length

Max length	61
Median length	13
Mean length	14.539
Min length	2

Characters and Unicode

Total characters	14539
Distinct characters	81
Distinct categories	8 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	998 ?
Unique (%)	99.8%

Sample

1st row	Guardians of the Galaxy
2nd row	Prometheus
3rd row	Split
4th row	Sing
5th row	Suicide Squad

Value	Count	Frequency (%)
The Host	2	0.2%
The Invitation	1	0.1%
La tortue rouge	1	0.1%
Big Hero 6	1	0.1%
Relatos salvajes	1	0.1%
True Crimes	1	0.1%
Steve Jobs	1	0.1%
It Follows	1	0.1%
Superbad	1	0.1%
Legend	1	0.1%
Other values (989)	989	98.9%

Histogram of lengths of the category

Value	Count	Frequency (%)
the	305	11.7%
of	92	3.5%
a	29	1.1%
and	22	0.8%
2	22	0.8%
in	22	0.8%
	15	0.6%
to	12	0.5%
man	12	0.5%
me	11	0.4%
Other values (1429)	2063	79.2%

Most occurring characters

Value	Count	Frequency (%)
	1605	11.0%
e	1507	10.4%
a	884	6.1%
o	851	5.9%
n	828	5.7%
r	799	5.5%
i	775	5.3%
t	720	5.0%
s	609	4.2%
h	539	3.7%
Other values (71)	5422	37.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	10340	71.1%
Uppercase Letter	2274	15.6%
Space Separator	1605	11.0%
Other Punctuation	171	1.2%
Decimal Number	110	0.8%
Dash Punctuation	31	0.2%
Open Punctuation	4	< 0.1%
Close Punctuation	4	< 0.1%

Most frequent character per category

Value	Count	Frequency (%)
e	1507	14.6%
a	884	8.5%
o	851	8.2%
n	828	8.0%
r	799	7.7%
i	775	7.5%
t	720	7.0%
s	609	5.9%
h	539	5.2%
l	457	4.4%
Other values (22)	2371	22.9%

Value	Count	Frequency (%)
T	350	15.4%
S	188	8.3%
M	141	6.2%
B	133	5.8%
D	125	5.5%
A	115	5.1%
P	110	4.8%
H	105	4.6%
C	104	4.6%
W	100	4.4%
Other values (16)	803	35.3%

Value	Count	Frequency (%)
2	35	31.8%
3	17	15.5%
1	15	13.6%
0	15	13.6%
5	7	6.4%
4	7	6.4%
7	5	4.5%
6	3	2.7%
9	3	2.7%
8	3	2.7%

Value	Count	Frequency (%)
:	85	49.7%
'	39	22.8%
.	23	13.5%
,	9	5.3%
&	6	3.5%
!	4	2.3%
?	2	1.2%
/	2	1.2%
·	1	0.6%

Value	Count	Frequency (%)
	1605	100.0%

Value	Count	Frequency (%)
-	31	100.0%

Value	Count	Frequency (%)
(	4	100.0%

Value	Count	Frequency (%)
)	4	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	12614	86.8%
Common	1925	13.2%

Most frequent character per script

Value	Count	Frequency (%)
e	1507	11.9%
a	884	7.0%
o	851	6.7%
n	828	6.6%
r	799	6.3%
i	775	6.1%
t	720	5.7%
s	609	4.8%
h	539	4.3%
l	457	3.6%
Other values (48)	4645	36.8%

Value	Count	Frequency (%)
	1605	83.4%
:	85	4.4%
'	39	2.0%
2	35	1.8%
-	31	1.6%
.	23	1.2%
3	17	0.9%
1	15	0.8%
0	15	0.8%
,	9	0.5%
Other values (13)	51	2.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	14530	99.9%
None	9	0.1%

Most frequent character per block

Value	Count	Frequency (%)
	1605	11.0%
e	1507	10.4%
a	884	6.1%
o	851	5.9%
n	828	5.7%
r	799	5.5%
i	775	5.3%
t	720	5.0%
s	609	4.2%
h	539	3.7%
Other values (64)	5413	37.3%

Value	Count	Frequency (%)
é	3	33.3%
è	1	11.1%
ä	1	11.1%
·	1	11.1%
í	1	11.1%
á	1	11.1%
ç	1	11.1%

genre
Categorical

HIGH CARDINALITY

Distinct	207
Distinct (%)	20.7%
Missing	0
Missing (%)	0.0%
Memory size	4.0 KiB

Action,Adventure,Sci-Fi	50
Drama	48
Comedy,Drama,Romance	35
Comedy	32
Drama,Romance	31
Other values (202)	804

Length

Max length	26
Median length	20
Mean length	18.095
Min length	5

Characters and Unicode

Total characters	18095
Distinct characters	31
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	85 ?
Unique (%)	8.5%

Sample

1st row	Action,Adventure,Sci-Fi
2nd row	Adventure,Mystery,Sci-Fi
3rd row	Horror,Thriller
4th row	Animation,Comedy,Family
5th row	Action,Adventure,Fantasy

Value	Count	Frequency (%)
Action,Adventure,Sci-Fi	50	5.0%
Drama	48	4.8%
Comedy,Drama,Romance	35	3.5%
Comedy	32	3.2%
Drama,Romance	31	3.1%
Animation,Adventure,Comedy	27	2.7%
Comedy,Drama	27	2.7%
Action,Adventure,Fantasy	27	2.7%
Comedy,Romance	26	2.6%
Crime,Drama,Thriller	24	2.4%
Other values (197)	673	67.3%

Histogram of lengths of the category

Value	Count	Frequency (%)
action,adventure,sci-fi	50	5.0%
drama	48	4.8%
comedy,drama,romance	35	3.5%
comedy	32	3.2%
drama,romance	31	3.1%
animation,adventure,comedy	27	2.7%
action,adventure,fantasy	27	2.7%
comedy,drama	27	2.7%
comedy,romance	26	2.6%
crime,drama,thriller	24	2.4%
Other values (197)	673	67.3%

Most occurring characters

Value	Count	Frequency (%)
r	1923	10.6%
a	1568	8.7%
,	1555	8.6%
e	1403	7.8%
m	1183	6.5%
i	1168	6.5%
o	1138	6.3%
n	909	5.0%
t	872	4.8%
y	753	4.2%
Other values (21)	5623	31.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	13745	76.0%
Uppercase Letter	2675	14.8%
Other Punctuation	1555	8.6%
Dash Punctuation	120	0.7%

Most frequent character per category

Value	Count	Frequency (%)
r	1923	14.0%
a	1568	11.4%
e	1403	10.2%
m	1183	8.6%
i	1168	8.5%
o	1138	8.3%
n	909	6.6%
t	872	6.3%
y	753	5.5%
c	585	4.3%
Other values (8)	2243	16.3%

Value	Count	Frequency (%)
A	611	22.8%
D	513	19.2%
C	429	16.0%
F	272	10.2%
T	195	7.3%
H	148	5.5%
R	141	5.3%
S	138	5.2%
M	127	4.7%
B	81	3.0%

Value	Count	Frequency (%)
,	1555	100.0%

Value	Count	Frequency (%)
-	120	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	16420	90.7%
Common	1675	9.3%

Most frequent character per script

Value	Count	Frequency (%)
r	1923	11.7%
a	1568	9.5%
e	1403	8.5%
m	1183	7.2%
i	1168	7.1%
o	1138	6.9%
n	909	5.5%
t	872	5.3%
y	753	4.6%
A	611	3.7%
Other values (19)	4892	29.8%

Value	Count	Frequency (%)
,	1555	92.8%
-	120	7.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	18095	100.0%

Most frequent character per block

Value	Count	Frequency (%)
r	1923	10.6%
a	1568	8.7%
,	1555	8.6%
e	1403	7.8%
m	1183	6.5%
i	1168	6.5%
o	1138	6.3%
n	909	5.0%
t	872	4.8%
y	753	4.2%
Other values (21)	5623	31.1%

description
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct	1000
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	4.0 KiB

A tight-knit team of rising investigators, along with their supervisor, is suddenly torn apart when they discover that one of their own teenage daughters has been brutally murdered.	1
Three buddies wake up from a bachelor party in Las Vegas, with no memory of the previous night and the bachelor missing. They make their way around the city in order to find their friend before his wedding.	1
In 1984 East Berlin, an agent of the secret police, conducting surveillance on a writer and his lover, finds himself becoming increasingly absorbed by their lives.	1
After an experimental bio-weapon is released, turning thousands into zombie-like creatures, it's up to a rag-tag group of survivors to stop the infected and those behind its release.	1
Brian O'Conner, back working for the FBI in Los Angeles, teams up with Dominic Toretto to bring down a heroin importer by infiltrating his operation.	1
Other values (995)	995

Length

Max length	421
Median length	159
Mean length	163.232
Min length	42

Characters and Unicode

Total characters	163232
Distinct characters	82
Distinct categories	10 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1000 ?
Unique (%)	100.0%

Sample

1st row	A group of intergalactic criminals are forced to work together to stop a fanatical warrior from taking control of the universe.
2nd row	Following clues to the origin of mankind, a team finds a structure on a distant moon, but they soon realize they are not alone.
3rd row	Three girls are kidnapped by a man with a diagnosed 23 distinct personalities. They must try to escape before the apparent emergence of a frightful new 24th.
4th row	In a city of humanoid animals, a hustling theater impresario's attempt to save his theater with a singing competition becomes grander than he anticipates even as its finalists' find that their lives will never be the same.
5th row	A secret government agency recruits some of the most dangerous incarcerated super-villains to form a defensive task force. Their first mission: save the world from the apocalypse.

Value	Count	Frequency (%)
A tight-knit team of rising investigators, along with their supervisor, is suddenly torn apart when they discover that one of their own teenage daughters has been brutally murdered.	1	0.1%
Three buddies wake up from a bachelor party in Las Vegas, with no memory of the previous night and the bachelor missing. They make their way around the city in order to find their friend before his wedding.	1	0.1%
In 1984 East Berlin, an agent of the secret police, conducting surveillance on a writer and his lover, finds himself becoming increasingly absorbed by their lives.	1	0.1%
After an experimental bio-weapon is released, turning thousands into zombie-like creatures, it's up to a rag-tag group of survivors to stop the infected and those behind its release.	1	0.1%
Brian O'Conner, back working for the FBI in Los Angeles, teams up with Dominic Toretto to bring down a heroin importer by infiltrating his operation.	1	0.1%
A head chef quits his restaurant job and buys a food truck in an effort to reclaim his creative promise, while piecing back together his estranged family.	1	0.1%
Newlywed couple Ted and Tami-Lynn want to have a baby, but in order to qualify to be a parent, Ted will have to prove he's a person in a court of law.	1	0.1%
In an emotionless utopia, two people fall in love when they regain their feelings from a mysterious disease, causing tensions between them and their society.	1	0.1%
When a member of a popular New York City improv troupe gets a huge break, the rest of the group - all best friends - start to realize that not everyone is going to make it after all.	1	0.1%
A grief-stricken mother takes on the LAPD to her own detriment when it stubbornly tries to pass off an obvious impostor as her missing child, while also refusing to give up hope that she will find him one day.	1	0.1%
Other values (990)	990	99.0%

Histogram of lengths of the category

Value	Count	Frequency (%)
a	1626	5.8%
the	1360	4.9%
to	934	3.3%
of	807	2.9%
and	716	2.6%
in	578	2.1%
his	487	1.7%
an	304	1.1%
is	296	1.1%
with	274	1.0%
Other values (6172)	20539	73.6%

Most occurring characters

Value	Count	Frequency (%)
	26921	16.5%
e	15840	9.7%
t	10926	6.7%
a	10686	6.5%
i	9657	5.9%
o	9618	5.9%
n	9602	5.9%
r	9227	5.7%
s	8727	5.3%
h	6513	4.0%
Other values (72)	45515	27.9%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	128516	78.7%
Space Separator	26921	16.5%
Uppercase Letter	3786	2.3%
Other Punctuation	2995	1.8%
Decimal Number	506	0.3%
Dash Punctuation	438	0.3%
Open Punctuation	24	< 0.1%
Close Punctuation	24	< 0.1%
Final Punctuation	20	< 0.1%
Currency Symbol	2	< 0.1%

Most frequent character per category

Value	Count	Frequency (%)
e	15840	12.3%
t	10926	8.5%
a	10686	8.3%
i	9657	7.5%
o	9618	7.5%
n	9602	7.5%
r	9227	7.2%
s	8727	6.8%
h	6513	5.1%
l	5169	4.0%
Other values (20)	32551	25.3%

Value	Count	Frequency (%)
A	688	18.2%
T	290	7.7%
S	271	7.2%
B	227	6.0%
W	211	5.6%
C	204	5.4%
I	201	5.3%
M	192	5.1%
F	142	3.8%
H	140	3.7%
Other values (16)	1220	32.2%

Value	Count	Frequency (%)
.	1365	45.6%
,	1216	40.6%
'	297	9.9%
"	66	2.2%
:	26	0.9%
?	11	0.4%
;	8	0.3%
/	4	0.1%
!	1	< 0.1%
#	1	< 0.1%

Value	Count	Frequency (%)
1	110	21.7%
0	108	21.3%
9	92	18.2%
2	53	10.5%
7	31	6.1%
8	28	5.5%
6	25	4.9%
4	23	4.5%
5	23	4.5%
3	13	2.6%

Value	Count	Frequency (%)
	26921	100.0%

Value	Count	Frequency (%)
-	438	100.0%

Value	Count	Frequency (%)
(	24	100.0%

Value	Count	Frequency (%)
)	24	100.0%

Value	Count	Frequency (%)
»	20	100.0%

Value	Count	Frequency (%)
$	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	132302	81.1%
Common	30930	18.9%

Most frequent character per script

Value	Count	Frequency (%)
e	15840	12.0%
t	10926	8.3%
a	10686	8.1%
i	9657	7.3%
o	9618	7.3%
n	9602	7.3%
r	9227	7.0%
s	8727	6.6%
h	6513	4.9%
l	5169	3.9%
Other values (46)	36337	27.5%

Value	Count	Frequency (%)
	26921	87.0%
.	1365	4.4%
,	1216	3.9%
-	438	1.4%
'	297	1.0%
1	110	0.4%
0	108	0.3%
9	92	0.3%
"	66	0.2%
2	53	0.2%
Other values (16)	264	0.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	163203	> 99.9%
None	29	< 0.1%

Most frequent character per block

Value	Count	Frequency (%)
	26921	16.5%
e	15840	9.7%
t	10926	6.7%
a	10686	6.5%
i	9657	5.9%
o	9618	5.9%
n	9602	5.9%
r	9227	5.7%
s	8727	5.3%
h	6513	4.0%
Other values (67)	45486	27.9%

Value	Count	Frequency (%)
»	20	69.0%
é	4	13.8%
á	2	6.9%
è	2	6.9%
í	1	3.4%

director
Categorical

HIGH CARDINALITY
UNIFORM

Distinct	644
Distinct (%)	64.4%
Missing	0
Missing (%)	0.0%
Memory size	4.0 KiB

Ridley Scott	8
David Yates	6
Michael Bay	6
Paul W.S. Anderson	6
M. Night Shyamalan	6
Other values (639)	968

Length

Max length	32
Median length	13
Mean length	13.139
Min length	3

Characters and Unicode

Total characters	13139
Distinct characters	69
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	444 ?
Unique (%)	44.4%

Sample

1st row	James Gunn
2nd row	Ridley Scott
3rd row	M. Night Shyamalan
4th row	Christophe Lourdelet
5th row	David Ayer

Value	Count	Frequency (%)
Ridley Scott	8	0.8%
David Yates	6	0.6%
Michael Bay	6	0.6%
Paul W.S. Anderson	6	0.6%
M. Night Shyamalan	6	0.6%
Antoine Fuqua	5	0.5%
Denis Villeneuve	5	0.5%
Danny Boyle	5	0.5%
Martin Scorsese	5	0.5%
Zack Snyder	5	0.5%
Other values (634)	943	94.3%

Histogram of lengths of the category

Value	Count	Frequency (%)
david	38	1.8%
john	25	1.2%
michael	22	1.1%
james	21	1.0%
scott	20	1.0%
paul	19	0.9%
robert	14	0.7%
steven	13	0.6%
lee	12	0.6%
peter	12	0.6%
Other values (977)	1896	90.6%

Most occurring characters

Value	Count	Frequency (%)
e	1223	9.3%
	1092	8.3%
a	1056	8.0%
n	937	7.1%
r	875	6.7%
o	783	6.0%
i	740	5.6%
l	604	4.6%
t	486	3.7%
s	467	3.6%
Other values (59)	4876	37.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	9802	74.6%
Uppercase Letter	2153	16.4%
Space Separator	1092	8.3%
Other Punctuation	73	0.6%
Dash Punctuation	19	0.1%

Most frequent character per category

Value	Count	Frequency (%)
e	1223	12.5%
a	1056	10.8%
n	937	9.6%
r	875	8.9%
o	783	8.0%
i	740	7.5%
l	604	6.2%
t	486	5.0%
s	467	4.8%
h	357	3.6%
Other values (28)	2274	23.2%

Value	Count	Frequency (%)
S	207	9.6%
J	200	9.3%
M	183	8.5%
A	148	6.9%
D	137	6.4%
G	131	6.1%
B	127	5.9%
C	123	5.7%
R	119	5.5%
L	108	5.0%
Other values (17)	670	31.1%

Value	Count	Frequency (%)
.	71	97.3%
'	2	2.7%

Value	Count	Frequency (%)
	1092	100.0%

Value	Count	Frequency (%)
-	19	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	11955	91.0%
Common	1184	9.0%

Most frequent character per script

Value	Count	Frequency (%)
e	1223	10.2%
a	1056	8.8%
n	937	7.8%
r	875	7.3%
o	783	6.5%
i	740	6.2%
l	604	5.1%
t	486	4.1%
s	467	3.9%
h	357	3.0%
Other values (55)	4427	37.0%

Value	Count	Frequency (%)
	1092	92.2%
.	71	6.0%
-	19	1.6%
'	2	0.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	13095	99.7%
None	44	0.3%

Most frequent character per block

Value	Count	Frequency (%)
e	1223	9.3%
	1092	8.3%
a	1056	8.1%
n	937	7.2%
r	875	6.7%
o	783	6.0%
i	740	5.7%
l	604	4.6%
t	486	3.7%
s	467	3.6%
Other values (46)	4832	36.9%

Value	Count	Frequency (%)
é	11	25.0%
á	9	20.5%
ó	4	9.1%
ö	4	9.1%
å	4	9.1%
ñ	3	6.8%
ç	3	6.8%
Ø	1	2.3%
í	1	2.3%
ë	1	2.3%
Other values (3)	3	6.8%

actors
Categorical

HIGH CARDINALITY
UNIFORM

Distinct	996
Distinct (%)	99.6%
Missing	0
Missing (%)	0.0%
Memory size	4.0 KiB

Gerard Butler, Aaron Eckhart, Morgan Freeman,Angela Bassett	2
Shia LaBeouf, Megan Fox, Josh Duhamel, Tyrese Gibson	2
Daniel Radcliffe, Emma Watson, Rupert Grint, Michael Gambon	2
Jennifer Lawrence, Josh Hutcherson, Liam Hemsworth, Woody Harrelson	2
Shia LaBeouf, David Morse, Carrie-Anne Moss, Sarah Roemer	1
Other values (991)	991

Length

Max length	77
Median length	58
Mean length	58.288
Min length	43

Characters and Unicode

Total characters	58288
Distinct characters	79
Distinct categories	6 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	992 ?
Unique (%)	99.2%

Sample

1st row	Chris Pratt, Vin Diesel, Bradley Cooper, Zoe Saldana
2nd row	Noomi Rapace, Logan Marshall-Green, Michael Fassbender, Charlize Theron
3rd row	James McAvoy, Anya Taylor-Joy, Haley Lu Richardson, Jessica Sula
4th row	Matthew McConaughey,Reese Witherspoon, Seth MacFarlane, Scarlett Johansson
5th row	Will Smith, Jared Leto, Margot Robbie, Viola Davis

Value	Count	Frequency (%)
Gerard Butler, Aaron Eckhart, Morgan Freeman,Angela Bassett	2	0.2%
Shia LaBeouf, Megan Fox, Josh Duhamel, Tyrese Gibson	2	0.2%
Daniel Radcliffe, Emma Watson, Rupert Grint, Michael Gambon	2	0.2%
Jennifer Lawrence, Josh Hutcherson, Liam Hemsworth, Woody Harrelson	2	0.2%
Shia LaBeouf, David Morse, Carrie-Anne Moss, Sarah Roemer	1	0.1%
Shailene Woodley, Ansel Elgort, Nat Wolff, Laura Dern	1	0.1%
Adam Sandler, Jennifer Aniston, Brooklyn Decker,Nicole Kidman	1	0.1%
Willem Dafoe, Charlotte Gainsbourg, Storm Acheche Sahlstrøm	1	0.1%
Steve Carell, Ryan Gosling, Julianne Moore, Emma Stone	1	0.1%
Tom Hardy, Noomi Rapace, James Gandolfini,Matthias Schoenaerts	1	0.1%
Other values (986)	986	98.6%

Histogram of lengths of the category

Value	Count	Frequency (%)
michael	62	0.8%
james	50	0.6%
tom	44	0.6%
chris	42	0.5%
john	42	0.5%
jason	41	0.5%
robert	37	0.5%
mark	35	0.4%
jennifer	35	0.4%
ben	31	0.4%
Other values (2924)	7441	94.7%

Most occurring characters

Value	Count	Frequency (%)
	6860	11.8%
e	5007	8.6%
a	4812	8.3%
n	3867	6.6%
i	3216	5.5%
r	3171	5.4%
,	2999	5.1%
o	2949	5.1%
l	2811	4.8%
s	1931	3.3%
Other values (69)	20665	35.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	39800	68.3%
Uppercase Letter	8428	14.5%
Space Separator	6860	11.8%
Other Punctuation	3117	5.3%
Dash Punctuation	81	0.1%
Decimal Number	2	< 0.1%

Most frequent character per category

Value	Count	Frequency (%)
e	5007	12.6%
a	4812	12.1%
n	3867	9.7%
i	3216	8.1%
r	3171	8.0%
o	2949	7.4%
l	2811	7.1%
s	1931	4.9%
t	1924	4.8%
h	1557	3.9%
Other values (33)	8555	21.5%

Value	Count	Frequency (%)
J	749	8.9%
M	725	8.6%
C	661	7.8%
S	632	7.5%
B	618	7.3%
A	520	6.2%
R	507	6.0%
D	473	5.6%
L	389	4.6%
H	385	4.6%
Other values (19)	2769	32.9%

Value	Count	Frequency (%)
,	2999	96.2%
.	91	2.9%
'	27	0.9%

Value	Count	Frequency (%)
5	1	50.0%
0	1	50.0%

Value	Count	Frequency (%)
	6860	100.0%

Value	Count	Frequency (%)
-	81	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	48228	82.7%
Common	10060	17.3%

Most frequent character per script

Value	Count	Frequency (%)
e	5007	10.4%
a	4812	10.0%
n	3867	8.0%
i	3216	6.7%
r	3171	6.6%
o	2949	6.1%
l	2811	5.8%
s	1931	4.0%
t	1924	4.0%
h	1557	3.2%
Other values (62)	16983	35.2%

Value	Count	Frequency (%)
	6860	68.2%
,	2999	29.8%
.	91	0.9%
-	81	0.8%
'	27	0.3%
5	1	< 0.1%
0	1	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	58177	99.8%
None	111	0.2%

Most frequent character per block

Value	Count	Frequency (%)
	6860	11.8%
e	5007	8.6%
a	4812	8.3%
n	3867	6.6%
i	3216	5.5%
r	3171	5.5%
,	2999	5.2%
o	2949	5.1%
l	2811	4.8%
s	1931	3.3%
Other values (49)	20554	35.3%

Value	Count	Frequency (%)
é	29	26.1%
ë	16	14.4%
á	12	10.8%
í	10	9.0%
å	10	9.0%
ü	6	5.4%
ñ	5	4.5%
è	4	3.6%
Ó	3	2.7%
ô	2	1.8%
Other values (10)	14	12.6%

year
Real number (ℝ_≥0)

Distinct	11
Distinct (%)	1.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	2012.783
Minimum	2006
Maximum	2016
Zeros	0
Zeros (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	2006
5-th percentile	2007
Q1	2010
median	2014
Q3	2016
95-th percentile	2016
Maximum	2016
Range	10
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	3.205961508
Coefficient of variation (CV)	0.00159280037
Kurtosis	-0.8219639755
Mean	2012.783
Median Absolute Deviation (MAD)	2
Skewness	-0.6898787091
Sum	2012783
Variance	10.27818919
Monotocity	Not monotonic

Histogram with fixed size bins (bins=11)

Value	Count	Frequency (%)
2016	297	29.7%
2015	127	12.7%
2014	98	9.8%
2013	91	9.1%
2012	64	6.4%
2011	63	6.3%
2010	60	6.0%
2007	53	5.3%
2008	52	5.2%
2009	51	5.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2006	44	4.4%
2007	53	5.3%
2008	52	5.2%
2009	51	5.1%
2010	60	6.0%

Value	Count	Frequency (%)
2016	297	29.7%
2015	127	12.7%
2014	98	9.8%
2013	91	9.1%
2012	64	6.4%

runtime (minutes)
Real number (ℝ_≥0)

Distinct	94
Distinct (%)	9.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	113.172
Minimum	66
Maximum	191
Zeros	0
Zeros (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	66
5-th percentile	88
Q1	100
median	111
Q3	123
95-th percentile	150
Maximum	191
Range	125
Interquartile range (IQR)	23

Descriptive statistics

Standard deviation	18.81090817
Coefficient of variation (CV)	0.1662152138
Kurtosis	0.8583211032
Mean	113.172
Median Absolute Deviation (MAD)	12
Skewness	0.8467127314
Sum	113172
Variance	353.8502663
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
108	31	3.1%
100	28	2.8%
117	27	2.7%
110	26	2.6%
106	26	2.6%
118	26	2.6%
102	25	2.5%
112	24	2.4%
104	23	2.3%
123	23	2.3%
Other values (84)	741	74.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
66	1	0.1%
73	2	0.2%
80	2	0.2%
81	5	0.5%
82	1	0.1%

Value	Count	Frequency (%)
191	1	0.1%
187	1	0.1%
180	3	0.3%
172	1	0.1%
170	1	0.1%

rating
Real number (ℝ_≥0)

Distinct	55
Distinct (%)	5.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	6.7232
Minimum	1.9
Maximum	9
Zeros	0
Zeros (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	1.9
5-th percentile	5.1
Q1	6.2
median	6.8
Q3	7.4
95-th percentile	8.1
Maximum	9
Range	7.1
Interquartile range (IQR)	1.2

Descriptive statistics

Standard deviation	0.9454287893
Coefficient of variation (CV)	0.1406218451
Kurtosis	1.322270288
Mean	6.7232
Median Absolute Deviation (MAD)	0.6
Skewness	-0.7431419408
Sum	6723.2
Variance	0.8938355956
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
7.1	52	5.2%
6.7	48	4.8%
7	46	4.6%
6.3	44	4.4%
6.6	42	4.2%
7.2	42	4.2%
7.3	42	4.2%
6.5	40	4.0%
7.8	40	4.0%
6.2	37	3.7%
Other values (45)	567	56.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1.9	1	0.1%
2.7	2	0.2%
3.2	1	0.1%
3.5	2	0.2%
3.7	2	0.2%

Value	Count	Frequency (%)
9	1	0.1%
8.8	2	0.2%
8.6	3	0.3%
8.5	6	0.6%
8.4	4	0.4%

votes
Real number (ℝ_≥0)

Distinct	997
Distinct (%)	99.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	169808.255
Minimum	61
Maximum	1791916
Zeros	0
Zeros (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	61
5-th percentile	1260.35
Q1	36309
median	110799
Q3	239909.75
95-th percentile	526551.85
Maximum	1791916
Range	1791855
Interquartile range (IQR)	203600.75

Descriptive statistics

Standard deviation	188762.6475
Coefficient of variation (CV)	1.111622327
Kurtosis	11.3126809
Mean	169808.255
Median Absolute Deviation (MAD)	88402
Skewness	2.507918483
Sum	169808255
Variance	3.56313371 × 10¹⁰
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1427	2	0.2%
97141	2	0.2%
291	2	0.2%
531112	1	0.1%
702	1	0.1%
47804	1	0.1%
226619	1	0.1%
76469	1	0.1%
125693	1	0.1%
174553	1	0.1%
Other values (987)	987	98.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
61	1	0.1%
96	1	0.1%
102	1	0.1%
115	1	0.1%
164	1	0.1%

Value	Count	Frequency (%)
1791916	1	0.1%
1583625	1	0.1%
1222645	1	0.1%
1047747	1	0.1%
1045588	1	0.1%

revenue (millions)
Real number (ℝ_≥0)

MISSING

Distinct	814
Distinct (%)	93.3%
Missing	128
Missing (%)	12.8%
Infinite	0
Infinite (%)	0.0%

Mean	82.95637615
Minimum	0
Maximum	936.63
Zeros	1
Zeros (%)	0.1%
Memory size	7.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0.211
Q1	13.27
median	47.985
Q3	113.715
95-th percentile	293.88
Maximum	936.63
Range	936.63
Interquartile range (IQR)	100.445

Descriptive statistics

Standard deviation	103.2535405
Coefficient of variation (CV)	1.244672746
Kurtosis	10.60763453
Mean	82.95637615
Median Absolute Deviation (MAD)	41.285
Skewness	2.592515866
Sum	72337.96
Variance	10661.29362
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.03	7	0.7%
0.01	5	0.5%
0.04	4	0.4%
0.02	4	0.4%
0.32	4	0.4%
0.05	4	0.4%
1.29	3	0.3%
0.15	3	0.3%
2.2	3	0.3%
0.54	3	0.3%
Other values (804)	832	83.2%
(Missing)	128	12.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.1%
0.01	5	0.5%
0.02	4	0.4%
0.03	7	0.7%
0.04	4	0.4%

Value	Count	Frequency (%)
936.63	1	0.1%
760.51	1	0.1%
652.18	1	0.1%
623.28	1	0.1%
533.32	1	0.1%

metascore
Real number (ℝ_≥0)

MISSING

Distinct	84
Distinct (%)	9.0%
Missing	64
Missing (%)	6.4%
Infinite	0
Infinite (%)	0.0%

Mean	58.98504274
Minimum	11
Maximum	100
Zeros	0
Zeros (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	11
5-th percentile	31
Q1	47
median	59.5
Q3	72
95-th percentile	85
Maximum	100
Range	89
Interquartile range (IQR)	25

Descriptive statistics

Standard deviation	17.19475702
Coefficient of variation (CV)	0.2915104614
Kurtosis	-0.6122051468
Mean	58.98504274
Median Absolute Deviation (MAD)	12.5
Skewness	-0.1238873467
Sum	55210
Variance	295.6596691
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
66	25	2.5%
72	25	2.5%
68	25	2.5%
64	24	2.4%
57	23	2.3%
51	22	2.2%
65	22	2.2%
48	21	2.1%
81	21	2.1%
76	21	2.1%
Other values (74)	707	70.7%
(Missing)	64	6.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
11	1	0.1%
15	1	0.1%
16	1	0.1%
18	4	0.4%
19	1	0.1%

Value	Count	Frequency (%)
100	1	0.1%
99	1	0.1%
98	1	0.1%
96	4	0.4%
95	3	0.3%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	rank	title	genre	description	director	actors	year	runtime (minutes)	rating	votes	revenue (millions)	metascore
0	1	Guardians of the Galaxy	Action,Adventure,Sci-Fi	A group of intergalactic criminals are forced to work together to stop a fanatical warrior from taking control of the universe.	James Gunn	Chris Pratt, Vin Diesel, Bradley Cooper, Zoe Saldana	2014	121	8.1	757074	333.13	76.0
1	2	Prometheus	Adventure,Mystery,Sci-Fi	Following clues to the origin of mankind, a team finds a structure on a distant moon, but they soon realize they are not alone.	Ridley Scott	Noomi Rapace, Logan Marshall-Green, Michael Fassbender, Charlize Theron	2012	124	7.0	485820	126.46	65.0
2	3	Split	Horror,Thriller	Three girls are kidnapped by a man with a diagnosed 23 distinct personalities. They must try to escape before the apparent emergence of a frightful new 24th.	M. Night Shyamalan	James McAvoy, Anya Taylor-Joy, Haley Lu Richardson, Jessica Sula	2016	117	7.3	157606	138.12	62.0
3	4	Sing	Animation,Comedy,Family	In a city of humanoid animals, a hustling theater impresario's attempt to save his theater with a singing competition becomes grander than he anticipates even as its finalists' find that their lives will never be the same.	Christophe Lourdelet	Matthew McConaughey,Reese Witherspoon, Seth MacFarlane, Scarlett Johansson	2016	108	7.2	60545	270.32	59.0
4	5	Suicide Squad	Action,Adventure,Fantasy	A secret government agency recruits some of the most dangerous incarcerated super-villains to form a defensive task force. Their first mission: save the world from the apocalypse.	David Ayer	Will Smith, Jared Leto, Margot Robbie, Viola Davis	2016	123	6.2	393727	325.02	40.0
5	6	The Great Wall	Action,Adventure,Fantasy	European mercenaries searching for black powder become embroiled in the defense of the Great Wall of China against a horde of monstrous creatures.	Yimou Zhang	Matt Damon, Tian Jing, Willem Dafoe, Andy Lau	2016	103	6.1	56036	45.13	42.0
6	7	La La Land	Comedy,Drama,Music	A jazz pianist falls for an aspiring actress in Los Angeles.	Damien Chazelle	Ryan Gosling, Emma Stone, Rosemarie DeWitt, J.K. Simmons	2016	128	8.3	258682	151.06	93.0
7	8	Mindhorn	Comedy	A has-been actor best known for playing the title character in the 1980s detective series "Mindhorn" must work with the police when a serial killer says that he will only speak with Detective Mindhorn, whom he believes to be a real person.	Sean Foley	Essie Davis, Andrea Riseborough, Julian Barratt,Kenneth Branagh	2016	89	6.4	2490	NaN	71.0
8	9	The Lost City of Z	Action,Adventure,Biography	A true-life drama, centering on British explorer Col. Percival Fawcett, who disappeared while searching for a mysterious city in the Amazon in the 1920s.	James Gray	Charlie Hunnam, Robert Pattinson, Sienna Miller, Tom Holland	2016	141	7.1	7188	8.01	78.0
9	10	Passengers	Adventure,Drama,Romance	A spacecraft traveling to a distant colony planet and transporting thousands of people has a malfunction in its sleep chambers. As a result, two passengers are awakened 90 years early.	Morten Tyldum	Jennifer Lawrence, Chris Pratt, Michael Sheen,Laurence Fishburne	2016	116	7.0	192177	100.01	41.0

Last rows

	rank	title	genre	description	director	actors	year	runtime (minutes)	rating	votes	revenue (millions)	metascore
990	991	Underworld: Rise of the Lycans	Action,Adventure,Fantasy	An origins story centered on the centuries-old feud between the race of aristocratic vampires and their onetime slaves, the Lycans.	Patrick Tatopoulos	Rhona Mitra, Michael Sheen, Bill Nighy, Steven Mackintosh	2009	92	6.6	129708	45.80	44.0
991	992	Taare Zameen Par	Drama,Family,Music	An eight-year-old boy is thought to be a lazy trouble-maker, until the new art teacher has the patience and compassion to discover the real problem behind his struggles in school.	Aamir Khan	Darsheel Safary, Aamir Khan, Tanay Chheda, Sachet Engineer	2007	165	8.5	102697	1.20	42.0
992	993	Take Me Home Tonight	Comedy,Drama,Romance	Four years after graduation, an awkward high school genius uses his sister's boyfriend's Labor Day party as the perfect opportunity to make his move on his high school crush.	Michael Dowse	Topher Grace, Anna Faris, Dan Fogler, Teresa Palmer	2011	97	6.3	45419	6.92	NaN
993	994	Resident Evil: Afterlife	Action,Adventure,Horror	While still out to destroy the evil Umbrella Corporation, Alice joins a group of survivors living in a prison surrounded by the infected who also want to relocate to the mysterious but supposedly unharmed safe haven known only as Arcadia.	Paul W.S. Anderson	Milla Jovovich, Ali Larter, Wentworth Miller,Kim Coates	2010	97	5.9	140900	60.13	37.0
994	995	Project X	Comedy	3 high school seniors throw a birthday party to make a name for themselves. As the night progresses, things spiral out of control as word of the party spreads.	Nima Nourizadeh	Thomas Mann, Oliver Cooper, Jonathan Daniel Brown, Dax Flame	2012	88	6.7	164088	54.72	48.0
995	996	Secret in Their Eyes	Crime,Drama,Mystery	A tight-knit team of rising investigators, along with their supervisor, is suddenly torn apart when they discover that one of their own teenage daughters has been brutally murdered.	Billy Ray	Chiwetel Ejiofor, Nicole Kidman, Julia Roberts, Dean Norris	2015	111	6.2	27585	NaN	45.0
996	997	Hostel: Part II	Horror	Three American college students studying abroad are lured to a Slovakian hostel, and discover the grim reality behind it.	Eli Roth	Lauren German, Heather Matarazzo, Bijou Phillips, Roger Bart	2007	94	5.5	73152	17.54	46.0
997	998	Step Up 2: The Streets	Drama,Music,Romance	Romantic sparks occur between two dance students from different backgrounds at the Maryland School of the Arts.	Jon M. Chu	Robert Hoffman, Briana Evigan, Cassie Ventura, Adam G. Sevani	2008	98	6.2	70699	58.01	50.0
998	999	Search Party	Adventure,Comedy	A pair of friends embark on a mission to reunite their pal with the woman he was going to marry.	Scot Armstrong	Adam Pally, T.J. Miller, Thomas Middleditch,Shannon Woodward	2014	93	5.6	4881	NaN	22.0
999	1000	Nine Lives	Comedy,Family,Fantasy	A stuffy businessman finds himself trapped inside the body of his family's cat.	Barry Sonnenfeld	Kevin Spacey, Jennifer Garner, Robbie Amell,Cheryl Hines	2016	87	5.3	12435	19.64	11.0

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Pearson's r

Spearman's ρ

Kendall's τ

Phik (φk)

Missing values

Sample

First rows

Last rows